Hi, all! The Machine Intelligence Research Institute (MIRI) is answering questions here tomorrow, October 12 at 10am PDT. You can post questions below in the interim.
MIRI is a Berkeley-based research nonprofit that does basic research on key technical questions related to smarter-than-human artificial intelligence systems. Our research is largely aimed at developing a deeper and more formal understanding of such systems and their safety requirements, so that the research community is better-positioned to design systems that can be aligned with our interests. See here for more background.
Through the end of October, we're running our 2016 fundraiser — our most ambitious funding drive to date. Part of the goal of this AMA is to address questions about our future plans and funding gap, but we're also hoping to get very general questions about AI risk, very specialized questions about our technical work, and everything in between. Some of the biggest news at MIRI since Nate's AMA here last year:
- We developed a new framework for thinking about deductively limited reasoning, logical induction.
- Half of our research team started work on a new machine learning research agenda, distinct from our agent foundations agenda.
- We received a review and a $500k grant from the Open Philanthropy Project.
Likely participants in the AMA include:
- Nate Soares, Executive Director and primary author of the AF research agenda
- Malo Bourgon, Chief Operating Officer
- Rob Bensinger, Research Communications Manager
- Jessica Taylor, Research Fellow and primary author of the ML research agenda
- Tsvi Benson-Tilsen, Research Associate
Nate, Jessica, and Tsvi are also three of the co-authors of the "Logical Induction" paper.
EDIT (10:04am PDT): We're here! Answers on the way!
EDIT (10:55pm PDT): Thanks for all the great questions! That's all for now, though we'll post a few more answers tomorrow to things we didn't get to. If you'd like to support our AI safety work, our fundraiser will be continuing through the end of October.
Do you share Open Phil's view that there is a > 10% chance of transformative AI (defined as in Open Phil's post) in the next 20 years? What signposts would alert you that transformative AI is near?
Relatedly, suppose that transformative AI will happen within about 20 years (not necessarily a self improving AGI). Can you explain how MIRI's research will be relevant in such a near-term scenario (e.g. if it happens by scaling up deep learning methods)?
I share Open Phil’s view on the probability of transformative AI in the next 20 years. The relevant signposts would be answers to questions like “how are current algorithms doing on tasks requiring various capabilities”, “how much did this performance depend on task-specific tweaking on the part of programmers”, “how much is performance projected to improve due to increasing hardware”, and “do many credible AI researchers think that we are close to transformative AI”.
In designing the new ML-focused agenda, we imagined a concrete hypothetical (which isn’t ... (read more)